Overview

Brought to you by YData

Dataset statistics

Number of variables42
Number of observations8888
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 MiB
Average record size in memory163.7 B

Variable types

Numeric10
Categorical2
Boolean30

Alerts

estado_civil_CASADO is highly overall correlated with estado_civil_SOLTEROHigh correlation
estado_civil_SOLTERO is highly overall correlated with estado_civil_CASADOHigh correlation
estado_cliente_ACTIVO is highly overall correlated with estado_cliente_PASIVO and 2 other fieldsHigh correlation
estado_cliente_PASIVO is highly overall correlated with estado_cliente_ACTIVO and 2 other fieldsHigh correlation
falta_pago_N is highly overall correlated with estado_cliente_ACTIVO and 3 other fieldsHigh correlation
falta_pago_Y is highly overall correlated with estado_cliente_ACTIVO and 3 other fieldsHigh correlation
genero_F is highly overall correlated with genero_MHigh correlation
genero_M is highly overall correlated with genero_FHigh correlation
importe_solicitado is highly overall correlated with pct_ingresoHigh correlation
limite_credito_tc is highly overall correlated with nivel_tarjeta_BlueHigh correlation
nivel_tarjeta_Blue is highly overall correlated with limite_credito_tc and 1 other fieldsHigh correlation
nivel_tarjeta_Silver is highly overall correlated with nivel_tarjeta_BlueHigh correlation
pct_ingreso is highly overall correlated with importe_solicitadoHigh correlation
situacion_vivienda_ALQUILER is highly overall correlated with situacion_vivienda_HIPOTECAHigh correlation
situacion_vivienda_HIPOTECA is highly overall correlated with situacion_vivienda_ALQUILERHigh correlation
tasa_interes is highly overall correlated with falta_pago_N and 1 other fieldsHigh correlation
situacion_vivienda_OTROS is highly imbalanced (96.3%) Imbalance
situacion_vivienda_PROPIA is highly imbalanced (63.8%) Imbalance
objetivo_credito_MEJORAS_HOGAR is highly imbalanced (57.6%) Imbalance
estado_civil_DESCONOCIDO is highly imbalanced (62.2%) Imbalance
estado_civil_DIVORCIADO is highly imbalanced (61.7%) Imbalance
nivel_educativo_POSGRADO_COMPLETO is highly imbalanced (72.9%) Imbalance
nivel_educativo_POSGRADO_INCOMPLETO is highly imbalanced (70.6%) Imbalance
nivel_tarjeta_Blue is highly imbalanced (64.2%) Imbalance
nivel_tarjeta_Gold is highly imbalanced (90.8%) Imbalance
nivel_tarjeta_Platinum is highly imbalanced (97.8%) Imbalance
nivel_tarjeta_Silver is highly imbalanced (69.6%) Imbalance
edad is highly skewed (γ1 = 29.30473016) Skewed
antiguedad_empleado has 1276 (14.4%) zeros Zeros
personas_a_cargo has 787 (8.9%) zeros Zeros

Reproduction

Analysis started2025-05-07 16:17:59.370629
Analysis finished2025-05-07 16:18:03.185971
Duration3.82 seconds
Software versionydata-profiling vv4.13.0
Download configurationconfig.json

Variables

edad
Real number (ℝ)

Skewed 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.578308
Minimum20
Maximum144
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size396.9 KiB
2025-05-07T18:18:03.201246image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile21
Q122
median23
Q325
95-th percentile26
Maximum144
Range124
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.5809173
Coefficient of variation (CV)0.10946151
Kurtosis1312.4899
Mean23.578308
Median Absolute Deviation (MAD)1
Skewness29.30473
Sum209564
Variance6.661134
MonotonicityNot monotonic
2025-05-07T18:18:03.222707image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
22 1937
21.8%
23 1925
21.7%
24 1697
19.1%
25 1444
16.2%
26 1184
13.3%
21 692
 
7.8%
20 6
 
0.1%
144 2
 
< 0.1%
123 1
 
< 0.1%
ValueCountFrequency (%)
20 6
 
0.1%
21 692
 
7.8%
22 1937
21.8%
23 1925
21.7%
24 1697
19.1%
25 1444
16.2%
26 1184
13.3%
123 1
 
< 0.1%
144 2
 
< 0.1%
ValueCountFrequency (%)
144 2
 
< 0.1%
123 1
 
< 0.1%
26 1184
13.3%
25 1444
16.2%
24 1697
19.1%
23 1925
21.7%
22 1937
21.8%
21 692
 
7.8%
20 6
 
0.1%

importe_solicitado
Real number (ℝ)

High correlation 

Distinct487
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8179.087
Minimum500
Maximum35000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size396.9 KiB
2025-05-07T18:18:03.248368image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum500
5-th percentile2000
Q14500
median6500
Q310000
95-th percentile20000
Maximum35000
Range34500
Interquartile range (IQR)5500

Descriptive statistics

Standard deviation5767.1606
Coefficient of variation (CV)0.70511056
Kurtosis2.3503363
Mean8179.087
Median Absolute Deviation (MAD)2500
Skewness1.5272961
Sum72695725
Variance33260141
MonotonicityNot monotonic
2025-05-07T18:18:03.278997image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5000 693
 
7.8%
6000 642
 
7.2%
8000 499
 
5.6%
7000 390
 
4.4%
4000 386
 
4.3%
10000 333
 
3.7%
3000 325
 
3.7%
20000 253
 
2.8%
12000 228
 
2.6%
9000 221
 
2.5%
Other values (477) 4918
55.3%
ValueCountFrequency (%)
500 3
 
< 0.1%
700 1
 
< 0.1%
750 1
 
< 0.1%
800 1
 
< 0.1%
900 1
 
< 0.1%
1000 122
1.4%
1050 1
 
< 0.1%
1100 1
 
< 0.1%
1150 1
 
< 0.1%
1200 60
0.7%
ValueCountFrequency (%)
35000 20
0.2%
34800 1
 
< 0.1%
34000 1
 
< 0.1%
33950 1
 
< 0.1%
33000 1
 
< 0.1%
32500 1
 
< 0.1%
32000 1
 
< 0.1%
31300 1
 
< 0.1%
31050 1
 
< 0.1%
30000 19
0.2%

duracion_credito
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size396.9 KiB
2
2997 
3
2947 
4
2944 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters8888
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row2
3rd row2
4th row4
5th row2

Common Values

ValueCountFrequency (%)
2 2997
33.7%
3 2947
33.2%
4 2944
33.1%

Length

2025-05-07T18:18:03.303996image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-07T18:18:03.317651image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
2 2997
33.7%
3 2947
33.2%
4 2944
33.1%

Most occurring characters

ValueCountFrequency (%)
2 2997
33.7%
3 2947
33.2%
4 2944
33.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8888
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 2997
33.7%
3 2947
33.2%
4 2944
33.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8888
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 2997
33.7%
3 2947
33.2%
4 2944
33.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8888
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 2997
33.7%
3 2947
33.2%
4 2944
33.1%

antiguedad_empleado
Real number (ℝ)

Zeros 

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.9318182
Minimum0
Maximum123
Zeros1276
Zeros (%)14.4%
Negative0
Negative (%)0.0%
Memory size396.9 KiB
2025-05-07T18:18:03.334494image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median4
Q36
95-th percentile9
Maximum123
Range123
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.3576886
Coefficient of variation (CV)0.85397859
Kurtosis354.18599
Mean3.9318182
Median Absolute Deviation (MAD)2
Skewness10.21741
Sum34946
Variance11.274072
MonotonicityNot monotonic
2025-05-07T18:18:03.353071image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 1276
14.4%
2 1159
13.0%
3 1038
11.7%
5 967
10.9%
6 921
10.4%
1 910
10.2%
4 773
8.7%
7 706
7.9%
8 526
5.9%
9 368
 
4.1%
Other values (3) 244
 
2.7%
ValueCountFrequency (%)
0 1276
14.4%
1 910
10.2%
2 1159
13.0%
3 1038
11.7%
4 773
8.7%
5 967
10.9%
6 921
10.4%
7 706
7.9%
8 526
5.9%
9 368
 
4.1%
ValueCountFrequency (%)
123 2
 
< 0.1%
11 23
 
0.3%
10 219
 
2.5%
9 368
 
4.1%
8 526
5.9%
7 706
7.9%
6 921
10.4%
5 967
10.9%
4 773
8.7%
3 1038
11.7%

ingresos
Real number (ℝ)

Distinct1620
Distinct (%)18.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50970.59
Minimum9600
Maximum500000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size396.9 KiB
2025-05-07T18:18:03.378267image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum9600
5-th percentile21000
Q134000
median47000
Q360000
95-th percentile97286
Maximum500000
Range490400
Interquartile range (IQR)26000

Descriptive statistics

Standard deviation28961.735
Coefficient of variation (CV)0.56820483
Kurtosis20.958965
Mean50970.59
Median Absolute Deviation (MAD)13000
Skewness3.3531045
Sum4.530266 × 108
Variance8.3878211 × 108
MonotonicityNot monotonic
2025-05-07T18:18:03.406870image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
60000 386
 
4.3%
30000 313
 
3.5%
50000 304
 
3.4%
40000 242
 
2.7%
45000 217
 
2.4%
55000 201
 
2.3%
65000 197
 
2.2%
48000 194
 
2.2%
36000 185
 
2.1%
42000 176
 
2.0%
Other values (1610) 6473
72.8%
ValueCountFrequency (%)
9600 3
 
< 0.1%
9840 1
 
< 0.1%
9900 1
 
< 0.1%
9960 1
 
< 0.1%
10000 9
0.1%
10560 1
 
< 0.1%
10668 1
 
< 0.1%
10800 3
 
< 0.1%
10980 1
 
< 0.1%
11000 3
 
< 0.1%
ValueCountFrequency (%)
500000 1
 
< 0.1%
306000 1
 
< 0.1%
300000 6
0.1%
287000 1
 
< 0.1%
280000 1
 
< 0.1%
277104 1
 
< 0.1%
275000 1
 
< 0.1%
260000 1
 
< 0.1%
259000 1
 
< 0.1%
255000 1
 
< 0.1%

pct_ingreso
Real number (ℝ)

High correlation 

Distinct69
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.17531728
Minimum0.01
Maximum0.77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size396.9 KiB
2025-05-07T18:18:03.524811image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.04
Q10.09
median0.15
Q30.23
95-th percentile0.39
Maximum0.77
Range0.76
Interquartile range (IQR)0.14

Descriptive statistics

Standard deviation0.10810067
Coefficient of variation (CV)0.6166002
Kurtosis1.1335342
Mean0.17531728
Median Absolute Deviation (MAD)0.07
Skewness1.0613359
Sum1558.22
Variance0.011685755
MonotonicityNot monotonic
2025-05-07T18:18:03.554554image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1 464
 
5.2%
0.13 406
 
4.6%
0.09 391
 
4.4%
0.11 387
 
4.4%
0.08 386
 
4.3%
0.15 380
 
4.3%
0.12 352
 
4.0%
0.14 348
 
3.9%
0.07 346
 
3.9%
0.17 335
 
3.8%
Other values (59) 5093
57.3%
ValueCountFrequency (%)
0.01 17
 
0.2%
0.02 82
 
0.9%
0.03 199
2.2%
0.04 249
2.8%
0.05 262
2.9%
0.06 304
3.4%
0.07 346
3.9%
0.08 386
4.3%
0.09 391
4.4%
0.1 464
5.2%
ValueCountFrequency (%)
0.77 1
 
< 0.1%
0.71 1
 
< 0.1%
0.69 2
< 0.1%
0.68 1
 
< 0.1%
0.67 1
 
< 0.1%
0.65 2
< 0.1%
0.64 3
< 0.1%
0.63 3
< 0.1%
0.61 2
< 0.1%
0.6 2
< 0.1%

tasa_interes
Real number (ℝ)

High correlation 

Distinct306
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.019373
Minimum5.42
Maximum22.11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size396.9 KiB
2025-05-07T18:18:03.582333image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum5.42
5-th percentile6.03
Q17.9
median10.99
Q313.47
95-th percentile16.29
Maximum22.11
Range16.69
Interquartile range (IQR)5.57

Descriptive statistics

Standard deviation3.1946868
Coefficient of variation (CV)0.28991547
Kurtosis-0.70341725
Mean11.019373
Median Absolute Deviation (MAD)2.5
Skewness0.18465298
Sum97940.19
Variance10.206024
MonotonicityNot monotonic
2025-05-07T18:18:03.610496image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.99 252
 
2.8%
7.51 227
 
2.6%
7.9 189
 
2.1%
7.49 187
 
2.1%
7.88 173
 
1.9%
5.42 171
 
1.9%
9.99 148
 
1.7%
11.49 143
 
1.6%
13.49 132
 
1.5%
11.71 132
 
1.5%
Other values (296) 7134
80.3%
ValueCountFrequency (%)
5.42 171
1.9%
5.79 106
1.2%
5.99 112
1.3%
6 6
 
0.1%
6.03 121
1.4%
6.17 59
 
0.7%
6.39 14
 
0.2%
6.54 72
0.8%
6.62 116
1.3%
6.76 61
 
0.7%
ValueCountFrequency (%)
22.11 1
< 0.1%
21.74 2
< 0.1%
21.36 1
< 0.1%
21.27 1
< 0.1%
21.21 1
< 0.1%
20.89 2
< 0.1%
20.62 1
< 0.1%
20.3 2
< 0.1%
20.25 1
< 0.1%
20.2 1
< 0.1%

estado_credito
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size396.9 KiB
0
6718 
1
2170 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters8888
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 6718
75.6%
1 2170
 
24.4%

Length

2025-05-07T18:18:03.635051image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-07T18:18:03.647572image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 6718
75.6%
1 2170
 
24.4%

Most occurring characters

ValueCountFrequency (%)
0 6718
75.6%
1 2170
 
24.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8888
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 6718
75.6%
1 2170
 
24.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8888
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 6718
75.6%
1 2170
 
24.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8888
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 6718
75.6%
1 2170
 
24.4%

antiguedad_cliente
Real number (ℝ)

Distinct44
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.890414
Minimum13
Maximum56
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size396.9 KiB
2025-05-07T18:18:03.666090image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile22
Q131
median36
Q340
95-th percentile50
Maximum56
Range43
Interquartile range (IQR)9

Descriptive statistics

Standard deviation7.996337
Coefficient of variation (CV)0.22279868
Kurtosis0.41174424
Mean35.890414
Median Absolute Deviation (MAD)4
Skewness-0.10174188
Sum318994
Variance63.941405
MonotonicityNot monotonic
2025-05-07T18:18:03.690486image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
36 2127
23.9%
37 317
 
3.6%
34 313
 
3.5%
38 305
 
3.4%
40 304
 
3.4%
39 302
 
3.4%
31 296
 
3.3%
33 278
 
3.1%
35 272
 
3.1%
30 262
 
2.9%
Other values (34) 4112
46.3%
ValueCountFrequency (%)
13 63
0.7%
14 15
 
0.2%
15 29
 
0.3%
16 28
 
0.3%
17 35
 
0.4%
18 49
0.6%
19 55
0.6%
20 68
0.8%
21 75
0.8%
22 93
1.0%
ValueCountFrequency (%)
56 94
1.1%
55 36
 
0.4%
54 48
 
0.5%
53 65
0.7%
52 56
 
0.6%
51 70
0.8%
50 83
0.9%
49 127
1.4%
48 137
1.5%
47 145
1.6%

gastos_ult_12m
Real number (ℝ)

Distinct4718
Distinct (%)53.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4428.0135
Minimum510
Maximum18484
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size396.9 KiB
2025-05-07T18:18:03.715805image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum510
5-th percentile1289
Q12163.75
median3912
Q34747.25
95-th percentile14230
Maximum18484
Range17974
Interquartile range (IQR)2583.5

Descriptive statistics

Standard deviation3426.1207
Coefficient of variation (CV)0.77373763
Kurtosis3.8108409
Mean4428.0135
Median Absolute Deviation (MAD)1313
Skewness2.0307557
Sum39356184
Variance11738303
MonotonicityNot monotonic
2025-05-07T18:18:03.745522image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4509 10
 
0.1%
4253 10
 
0.1%
2229 9
 
0.1%
4518 9
 
0.1%
4037 8
 
0.1%
4674 8
 
0.1%
4275 8
 
0.1%
4498 8
 
0.1%
1731 8
 
0.1%
4348 8
 
0.1%
Other values (4708) 8802
99.0%
ValueCountFrequency (%)
510 1
< 0.1%
530 1
< 0.1%
563 1
< 0.1%
569 1
< 0.1%
594 1
< 0.1%
596 1
< 0.1%
597 1
< 0.1%
615 1
< 0.1%
643 1
< 0.1%
644 1
< 0.1%
ValueCountFrequency (%)
18484 1
< 0.1%
17995 1
< 0.1%
17744 1
< 0.1%
17634 1
< 0.1%
17628 1
< 0.1%
17498 1
< 0.1%
17437 1
< 0.1%
17390 1
< 0.1%
17350 1
< 0.1%
17258 1
< 0.1%

limite_credito_tc
Real number (ℝ)

High correlation 

Distinct5674
Distinct (%)63.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8607.8521
Minimum1438.3
Maximum34516
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size396.9 KiB
2025-05-07T18:18:03.772763image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1438.3
5-th percentile1438.3
Q12548
median4544.5
Q311046.25
95-th percentile34516
Maximum34516
Range33077.7
Interquartile range (IQR)8498.25

Descriptive statistics

Standard deviation9064.2945
Coefficient of variation (CV)1.0530263
Kurtosis1.8441154
Mean8607.8521
Median Absolute Deviation (MAD)2598.5
Skewness1.6729252
Sum76506590
Variance82161434
MonotonicityNot monotonic
2025-05-07T18:18:03.802578image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1438.3 453
 
5.1%
34516 449
 
5.1%
15987 18
 
0.2%
9959 14
 
0.2%
6224 11
 
0.1%
23981 11
 
0.1%
3735 10
 
0.1%
2490 10
 
0.1%
7469 9
 
0.1%
14938 7
 
0.1%
Other values (5664) 7896
88.8%
ValueCountFrequency (%)
1438.3 453
5.1%
1439 2
 
< 0.1%
1440 1
 
< 0.1%
1441 2
 
< 0.1%
1442 1
 
< 0.1%
1443 3
 
< 0.1%
1446 1
 
< 0.1%
1449 2
 
< 0.1%
1451 2
 
< 0.1%
1452 2
 
< 0.1%
ValueCountFrequency (%)
34516 449
5.1%
34496 1
 
< 0.1%
34458 1
 
< 0.1%
34427 1
 
< 0.1%
34198 1
 
< 0.1%
34173 1
 
< 0.1%
34162 1
 
< 0.1%
34140 1
 
< 0.1%
34058 1
 
< 0.1%
33996 1
 
< 0.1%

personas_a_cargo
Real number (ℝ)

Zeros 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3518227
Minimum0
Maximum5
Zeros787
Zeros (%)8.9%
Negative0
Negative (%)0.0%
Memory size396.9 KiB
2025-05-07T18:18:03.825101image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile4
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.300598
Coefficient of variation (CV)0.55301703
Kurtosis-0.6893843
Mean2.3518227
Median Absolute Deviation (MAD)1
Skewness-0.022036342
Sum20903
Variance1.6915551
MonotonicityNot monotonic
2025-05-07T18:18:03.842766image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 2390
26.9%
2 2321
26.1%
1 1615
18.2%
4 1399
15.7%
0 787
 
8.9%
5 376
 
4.2%
ValueCountFrequency (%)
0 787
 
8.9%
1 1615
18.2%
2 2321
26.1%
3 2390
26.9%
4 1399
15.7%
5 376
 
4.2%
ValueCountFrequency (%)
5 376
 
4.2%
4 1399
15.7%
3 2390
26.9%
2 2321
26.1%
1 1615
18.2%
0 787
 
8.9%

situacion_vivienda_ALQUILER
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size336.2 KiB
True
5434 
False
3454 
ValueCountFrequency (%)
True 5434
61.1%
False 3454
38.9%
2025-05-07T18:18:03.856529image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

situacion_vivienda_HIPOTECA
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size336.2 KiB
False
6082 
True
2806 
ValueCountFrequency (%)
False 6082
68.4%
True 2806
31.6%
2025-05-07T18:18:03.866406image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

situacion_vivienda_OTROS
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size336.2 KiB
False
8853 
True
 
35
ValueCountFrequency (%)
False 8853
99.6%
True 35
 
0.4%
2025-05-07T18:18:03.876421image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

situacion_vivienda_PROPIA
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size336.2 KiB
False
8275 
True
 
613
ValueCountFrequency (%)
False 8275
93.1%
True 613
 
6.9%
2025-05-07T18:18:03.885615image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size336.2 KiB
False
6821 
True
2067 
ValueCountFrequency (%)
False 6821
76.7%
True 2067
 
23.3%
2025-05-07T18:18:03.895726image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size336.2 KiB
False
7368 
True
1520 
ValueCountFrequency (%)
False 7368
82.9%
True 1520
 
17.1%
2025-05-07T18:18:03.905695image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size336.2 KiB
False
8120 
True
 
768
ValueCountFrequency (%)
False 8120
91.4%
True 768
 
8.6%
2025-05-07T18:18:03.915583image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size336.2 KiB
False
7426 
True
1462 
ValueCountFrequency (%)
False 7426
83.6%
True 1462
 
16.4%
2025-05-07T18:18:03.925709image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size336.2 KiB
False
7431 
True
1457 
ValueCountFrequency (%)
False 7431
83.6%
True 1457
 
16.4%
2025-05-07T18:18:03.937246image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size336.2 KiB
False
7274 
True
1614 
ValueCountFrequency (%)
False 7274
81.8%
True 1614
 
18.2%
2025-05-07T18:18:03.947364image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

falta_pago_N
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size336.2 KiB
True
7323 
False
1565 
ValueCountFrequency (%)
True 7323
82.4%
False 1565
 
17.6%
2025-05-07T18:18:03.957809image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

falta_pago_Y
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size336.2 KiB
False
7323 
True
1565 
ValueCountFrequency (%)
False 7323
82.4%
True 1565
 
17.6%
2025-05-07T18:18:03.967803image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

estado_civil_CASADO
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size336.2 KiB
False
4784 
True
4104 
ValueCountFrequency (%)
False 4784
53.8%
True 4104
46.2%
2025-05-07T18:18:03.978370image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

estado_civil_DESCONOCIDO
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size336.2 KiB
False
8236 
True
 
652
ValueCountFrequency (%)
False 8236
92.7%
True 652
 
7.3%
2025-05-07T18:18:03.987980image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

estado_civil_DIVORCIADO
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size336.2 KiB
False
8224 
True
 
664
ValueCountFrequency (%)
False 8224
92.5%
True 664
 
7.5%
2025-05-07T18:18:03.997178image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

estado_civil_SOLTERO
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size336.2 KiB
False
5420 
True
3468 
ValueCountFrequency (%)
False 5420
61.0%
True 3468
39.0%
2025-05-07T18:18:04.006599image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

estado_cliente_ACTIVO
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size336.2 KiB
True
7443 
False
1445 
ValueCountFrequency (%)
True 7443
83.7%
False 1445
 
16.3%
2025-05-07T18:18:04.017611image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

estado_cliente_PASIVO
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size336.2 KiB
False
7443 
True
1445 
ValueCountFrequency (%)
False 7443
83.7%
True 1445
 
16.3%
2025-05-07T18:18:04.027816image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

genero_F
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size336.2 KiB
True
4722 
False
4166 
ValueCountFrequency (%)
True 4722
53.1%
False 4166
46.9%
2025-05-07T18:18:04.038362image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

genero_M
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size336.2 KiB
False
4722 
True
4166 
ValueCountFrequency (%)
False 4722
53.1%
True 4166
46.9%
2025-05-07T18:18:04.049629image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size336.2 KiB
False
7574 
True
1314 
ValueCountFrequency (%)
False 7574
85.2%
True 1314
 
14.8%
2025-05-07T18:18:04.059599image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size336.2 KiB
False
8475 
True
 
413
ValueCountFrequency (%)
False 8475
95.4%
True 413
 
4.6%
2025-05-07T18:18:04.069429image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size336.2 KiB
False
8427 
True
 
461
ValueCountFrequency (%)
False 8427
94.8%
True 461
 
5.2%
2025-05-07T18:18:04.078546image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size336.2 KiB
False
7125 
True
1763 
ValueCountFrequency (%)
False 7125
80.2%
True 1763
 
19.8%
2025-05-07T18:18:04.088827image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size336.2 KiB
False
6144 
True
2744 
ValueCountFrequency (%)
False 6144
69.1%
True 2744
30.9%
2025-05-07T18:18:04.099230image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size336.2 KiB
False
6695 
True
2193 
ValueCountFrequency (%)
False 6695
75.3%
True 2193
 
24.7%
2025-05-07T18:18:04.109574image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

nivel_tarjeta_Blue
Boolean

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size336.2 KiB
True
8284 
False
 
604
ValueCountFrequency (%)
True 8284
93.2%
False 604
 
6.8%
2025-05-07T18:18:04.119530image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

nivel_tarjeta_Gold
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size336.2 KiB
False
8784 
True
 
104
ValueCountFrequency (%)
False 8784
98.8%
True 104
 
1.2%
2025-05-07T18:18:04.129705image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

nivel_tarjeta_Platinum
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size336.2 KiB
False
8869 
True
 
19
ValueCountFrequency (%)
False 8869
99.8%
True 19
 
0.2%
2025-05-07T18:18:04.138626image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

nivel_tarjeta_Silver
Boolean

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size336.2 KiB
False
8407 
True
 
481
ValueCountFrequency (%)
False 8407
94.6%
True 481
 
5.4%
2025-05-07T18:18:04.147747image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Interactions

2025-05-07T18:18:02.772775image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:00.407922image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:00.677673image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:00.929066image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.171500image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.410816image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.668558image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.921640image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.244281image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.523237image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.795858image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:00.431913image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:00.702828image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:00.952195image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.194424image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.436938image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.693883image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.944661image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.268599image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.548227image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.819315image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:00.456054image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:00.727589image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:00.977020image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.220200image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.463702image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.719322image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.065896image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.294182image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.573962image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.844238image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:00.479753image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:00.753187image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.000220image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.243558image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.489032image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.745695image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.087538image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.318275image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.599240image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.866538image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:00.503208image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:00.777700image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.023500image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.266566image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.514673image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.770015image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.109627image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.343251image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.624198image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.892230image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:00.529074image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:00.804400image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.050047image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.291280image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.540958image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.797196image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.133349image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.369247image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.649767image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.915735image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:00.552587image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:00.830011image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.074421image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.317342image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.567185image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.822373image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.156140image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.421375image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.675386image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.938077image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:00.574547image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:00.854097image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.096499image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.339177image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.591090image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.846438image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.175536image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.448145image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.698449image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.962406image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:00.598338image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:00.879531image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.122233image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.363602image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.617538image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.871677image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.198989image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.473694image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.723269image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.987297image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:00.653963image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:00.905125image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.147658image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.388200image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.644435image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:01.897846image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.221837image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.498845image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-07T18:18:02.748847image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-05-07T18:18:04.176037image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
antiguedad_clienteantiguedad_empleadoduracion_creditoedadestado_civil_CASADOestado_civil_DESCONOCIDOestado_civil_DIVORCIADOestado_civil_SOLTEROestado_cliente_ACTIVOestado_cliente_PASIVOestado_creditofalta_pago_Nfalta_pago_Ygastos_ult_12mgenero_Fgenero_Mimporte_solicitadoingresoslimite_credito_tcnivel_educativo_DESCONOCIDOnivel_educativo_POSGRADO_COMPLETOnivel_educativo_POSGRADO_INCOMPLETOnivel_educativo_SECUNDARIO_COMPLETOnivel_educativo_UNIVERSITARIO_COMPLETOnivel_educativo_UNIVERSITARIO_INCOMPLETOnivel_tarjeta_Bluenivel_tarjeta_Goldnivel_tarjeta_Platinumnivel_tarjeta_Silverobjetivo_credito_EDUCACIÓNobjetivo_credito_INVERSIONESobjetivo_credito_MEJORAS_HOGARobjetivo_credito_PAGO_DEUDASobjetivo_credito_PERSONALobjetivo_credito_SALUDpct_ingresopersonas_a_cargosituacion_vivienda_ALQUILERsituacion_vivienda_HIPOTECAsituacion_vivienda_OTROSsituacion_vivienda_PROPIAtasa_interes
antiguedad_cliente1.000-0.0010.000-0.0000.0480.0360.0400.0510.0320.0320.0250.0500.050-0.0250.0180.0180.0380.0140.0090.0000.0220.0290.0000.0230.0090.0290.0190.0000.0080.0000.0000.0120.0320.0160.0000.033-0.1150.0300.0330.0000.0000.009
antiguedad_empleado-0.0011.0000.0000.1090.0000.0000.0000.0000.0000.0000.0000.0000.0000.0630.0000.0000.1200.188-0.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000-0.002-0.0020.0000.0000.0000.000-0.065
duracion_credito0.0000.0001.0000.0000.0000.0000.0150.0000.0050.0050.0000.0000.0000.0000.0000.0000.0000.0000.0070.0080.0160.0000.0000.0320.0250.0200.0000.0000.0220.0000.0000.0090.0130.0220.0230.0000.0160.0060.0120.0000.0000.017
edad-0.0000.1090.0001.0000.0120.0000.0000.0100.0000.0000.0000.0000.0000.0090.0000.0000.0780.1560.0110.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0150.0000.0000.0000.0000.000-0.0370.0010.0000.0000.0000.0000.005
estado_civil_CASADO0.0480.0000.0000.0121.0000.2600.2630.7410.0250.0250.0430.0000.0000.1750.0000.0000.0900.0240.0640.0050.0000.0000.0000.0130.0140.0510.0170.0030.0440.0190.0140.0100.0000.0000.0000.0560.0220.0170.0130.0080.0000.000
estado_civil_DESCONOCIDO0.0360.0000.0000.0000.2601.0000.0780.2240.0000.0000.0190.0000.0000.0560.0110.0110.0420.0330.0170.0000.0000.0080.0000.0000.0000.0180.0110.0000.0090.0060.0000.0000.0000.0000.0000.0000.0390.0130.0040.0000.0000.011
estado_civil_DIVORCIADO0.0400.0000.0150.0000.2630.0781.0000.2270.0000.0000.0000.0000.0000.0390.0000.0000.0000.0000.0210.0160.0000.0000.0090.0000.0340.0000.0080.0000.0000.0000.0190.0000.0000.0000.0000.0120.0300.0000.0000.0000.0000.026
estado_civil_SOLTERO0.0510.0000.0000.0100.7410.2240.2271.0000.0170.0170.0320.0000.0000.1420.0130.0130.0680.0100.0330.0200.0000.0000.0000.0050.0000.0420.0160.0000.0340.0070.0000.0150.0000.0000.0060.0380.0380.0220.0170.0000.0000.000
estado_cliente_ACTIVO0.0320.0000.0050.0000.0250.0000.0000.0171.0001.0000.1170.5510.5510.3280.0310.0310.1060.0190.0340.0070.0310.0000.0060.0000.0000.0000.0000.0000.0000.0150.0000.0210.0000.0000.0000.0400.0190.0510.0530.0000.0000.319
estado_cliente_PASIVO0.0320.0000.0050.0000.0250.0000.0000.0171.0001.0000.1170.5510.5510.3280.0310.0310.1060.0190.0340.0070.0310.0000.0060.0000.0000.0000.0000.0000.0000.0150.0000.0210.0000.0000.0000.0400.0190.0510.0530.0000.0000.319
estado_credito0.0250.0000.0000.0000.0430.0190.0000.0320.1170.1171.0000.1920.1920.2320.0260.0260.2110.1170.0000.0000.0060.0090.0080.0000.0000.0000.0000.0000.0000.0960.0640.1110.0620.0130.0420.4040.0000.2070.1650.0230.1010.384
falta_pago_N0.0500.0000.0000.0000.0000.0000.0000.0000.5510.5510.1921.0001.0000.2610.0000.0000.0560.0000.0290.0000.0000.0000.0070.0040.0000.0000.0000.0000.0000.0140.0180.0490.0030.0000.0000.0430.0160.0720.0740.0120.0000.561
falta_pago_Y0.0500.0000.0000.0000.0000.0000.0000.0000.5510.5510.1921.0001.0000.2610.0000.0000.0560.0000.0290.0000.0000.0000.0070.0040.0000.0000.0000.0000.0000.0140.0180.0490.0030.0000.0000.0430.0160.0720.0740.0120.0000.561
gastos_ult_12m-0.0250.0630.0000.0090.1750.0560.0390.1420.3280.3280.2320.2610.2611.0000.2470.2470.0340.1560.0270.0210.0130.0000.0430.0000.0000.2440.1550.0750.1960.0110.0130.0000.0000.0000.000-0.0710.0590.1520.1810.0000.037-0.187
genero_F0.0180.0000.0000.0000.0000.0110.0000.0130.0310.0310.0260.0000.0000.2471.0001.0000.1700.1130.4420.0000.0070.0000.0130.0000.0000.0850.0380.0000.0740.0090.0000.0000.0000.0000.0070.0710.0000.0400.0420.0000.0000.002
genero_M0.0180.0000.0000.0000.0000.0110.0000.0130.0310.0310.0260.0000.0000.2471.0001.0000.1700.1130.4420.0000.0070.0000.0130.0000.0000.0850.0380.0000.0740.0090.0000.0000.0000.0000.0070.0710.0000.0400.0420.0000.0000.002
importe_solicitado0.0380.1200.0000.0780.0900.0420.0000.0680.1060.1060.2110.0560.0560.0340.1700.1701.0000.3500.0390.0270.0050.0000.0000.0200.0000.0800.0350.0160.0650.0000.0170.0320.0000.0000.0450.7400.0310.1900.1690.0120.0560.073
ingresos0.0140.1880.0000.1560.0240.0330.0000.0100.0190.0190.1170.0000.0000.1560.1130.1130.3501.0000.0370.0150.0000.0000.0240.0000.0140.0920.0550.0270.0670.0000.0210.0580.0450.0200.034-0.2930.0190.1560.1200.0000.086-0.027
limite_credito_tc0.009-0.0040.0070.0110.0640.0170.0210.0330.0340.0340.0000.0290.0290.0270.4420.4420.0390.0371.0000.0000.0060.0000.0000.0000.0170.5590.2880.1350.4740.0210.0000.0000.0000.0060.0000.0210.0490.0000.0230.0000.0100.003
nivel_educativo_DESCONOCIDO0.0000.0000.0080.0000.0050.0000.0160.0200.0070.0070.0000.0000.0000.0210.0000.0000.0270.0150.0001.0000.0910.0960.2070.2780.2380.0000.0000.0000.0000.0000.0000.0220.0190.0000.0000.0000.0290.0100.0000.0000.0140.000
nivel_educativo_POSGRADO_COMPLETO0.0220.0000.0160.0000.0000.0000.0000.0000.0310.0310.0060.0000.0000.0130.0070.0070.0050.0000.0060.0911.0000.0490.1090.1470.1250.0000.0000.0000.0000.0000.0000.0180.0000.0000.0000.0200.0000.0000.0000.0000.0000.012
nivel_educativo_POSGRADO_INCOMPLETO0.0290.0000.0000.0000.0000.0080.0000.0000.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.0000.0960.0491.0000.1150.1550.1330.0000.0000.0130.0000.0000.0170.0040.0000.0060.0000.0080.0130.0000.0000.0000.0040.000
nivel_educativo_SECUNDARIO_COMPLETO0.0000.0000.0000.0000.0000.0000.0090.0000.0060.0060.0080.0070.0070.0430.0130.0130.0000.0240.0000.2070.1090.1151.0000.3320.2840.0070.0000.0090.0000.0000.0000.0000.0000.0000.0160.0080.0110.0050.0000.0000.0000.010
nivel_educativo_UNIVERSITARIO_COMPLETO0.0230.0000.0320.0080.0130.0000.0000.0050.0000.0000.0000.0040.0040.0000.0000.0000.0200.0000.0000.2780.1470.1550.3321.0000.3820.0010.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0110.000
nivel_educativo_UNIVERSITARIO_INCOMPLETO0.0090.0000.0250.0000.0140.0000.0340.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0140.0170.2380.1250.1330.2840.3821.0000.0000.0000.0060.0000.0140.0000.0060.0000.0000.0060.0000.0150.0040.0040.0000.0000.000
nivel_tarjeta_Blue0.0290.0000.0200.0000.0510.0180.0000.0420.0000.0000.0000.0000.0000.2440.0850.0850.0800.0920.5590.0000.0000.0000.0070.0010.0001.0000.4010.1660.8850.0000.0000.0000.0000.0000.0000.0220.0300.0170.0260.0000.0070.000
nivel_tarjeta_Gold0.0190.0000.0000.0000.0170.0110.0080.0160.0000.0000.0000.0000.0000.1550.0380.0380.0350.0550.2880.0000.0000.0000.0000.0000.0000.4011.0000.0000.0210.0000.0000.0000.0000.0000.0000.0000.0290.0000.0070.0000.0030.019
nivel_tarjeta_Platinum0.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0750.0000.0000.0160.0270.1350.0000.0000.0130.0090.0000.0060.1660.0001.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.000
nivel_tarjeta_Silver0.0080.0000.0220.0000.0440.0090.0000.0340.0000.0000.0000.0000.0000.1960.0740.0740.0650.0670.4740.0000.0000.0000.0000.0000.0000.8850.0210.0001.0000.0000.0000.0000.0000.0070.0000.0250.0150.0160.0190.0000.0000.000
objetivo_credito_EDUCACIÓN0.0000.0000.0000.0150.0190.0060.0000.0070.0150.0150.0960.0140.0140.0110.0090.0090.0000.0000.0210.0000.0000.0000.0000.0000.0140.0000.0000.0000.0001.0000.2490.1680.2440.2430.2590.0000.0000.0000.0000.0000.0000.035
objetivo_credito_INVERSIONES0.0000.0000.0000.0000.0140.0000.0190.0000.0000.0000.0640.0180.0180.0130.0000.0000.0170.0210.0000.0000.0000.0170.0000.0000.0000.0000.0000.0000.0000.2491.0000.1390.2010.2000.2130.0280.0000.0450.0000.0000.0920.030
objetivo_credito_MEJORAS_HOGAR0.0120.0000.0090.0000.0100.0000.0000.0150.0210.0210.1110.0490.0490.0000.0000.0000.0320.0580.0000.0220.0180.0040.0000.0000.0060.0000.0000.0000.0000.1680.1391.0000.1360.1350.1440.0400.0230.0340.0270.0000.0080.047
objetivo_credito_PAGO_DEUDAS0.0320.0000.0130.0000.0000.0000.0000.0000.0000.0000.0620.0030.0030.0000.0000.0000.0000.0450.0000.0190.0000.0000.0000.0000.0000.0000.0000.0000.0000.2440.2010.1361.0000.1960.2080.0000.0130.0430.0000.0000.0920.015
objetivo_credito_PERSONAL0.0160.0000.0220.0000.0000.0000.0000.0000.0000.0000.0130.0000.0000.0000.0000.0000.0000.0200.0060.0000.0000.0060.0000.0000.0000.0000.0000.0000.0070.2430.2000.1350.1961.0000.2080.0000.0350.0160.0200.0000.0000.016
objetivo_credito_SALUD0.0000.0000.0230.0000.0000.0000.0000.0060.0000.0000.0420.0000.0000.0000.0070.0070.0450.0340.0000.0000.0000.0000.0160.0000.0060.0000.0000.0070.0000.2590.2130.1440.2080.2081.0000.0000.0000.0400.0380.0000.0000.027
pct_ingreso0.033-0.0020.000-0.0370.0560.0000.0120.0380.0400.0400.4040.0430.043-0.0710.0710.0710.740-0.2930.0210.0000.0200.0080.0080.0000.0000.0220.0000.0000.0250.0000.0280.0400.0000.0000.0001.0000.0220.0510.0300.0270.0490.092
personas_a_cargo-0.115-0.0020.0160.0010.0220.0390.0300.0380.0190.0190.0000.0160.0160.0590.0000.0000.0310.0190.0490.0290.0000.0130.0110.0000.0150.0300.0290.0000.0150.0000.0000.0230.0130.0350.0000.0221.0000.0000.0000.0000.014-0.010
situacion_vivienda_ALQUILER0.0300.0000.0060.0000.0170.0130.0000.0220.0510.0510.2070.0720.0720.1520.0400.0400.1900.1560.0000.0100.0000.0000.0050.0030.0040.0170.0000.0000.0160.0000.0450.0340.0430.0160.0400.0510.0001.0000.8520.0760.3410.144
situacion_vivienda_HIPOTECA0.0330.0000.0120.0000.0130.0040.0000.0170.0530.0530.1650.0740.0740.1810.0420.0420.1690.1200.0230.0000.0000.0000.0000.0000.0040.0260.0070.0000.0190.0000.0000.0270.0000.0200.0380.0300.0000.8521.0000.0390.1840.149
situacion_vivienda_OTROS0.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0230.0120.0120.0000.0000.0000.0120.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0270.0000.0760.0391.0000.0080.028
situacion_vivienda_PROPIA0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.1010.0000.0000.0370.0000.0000.0560.0860.0100.0140.0000.0040.0000.0110.0000.0070.0030.0000.0000.0000.0920.0080.0920.0000.0000.0490.0140.3410.1840.0081.0000.000
tasa_interes0.009-0.0650.0170.0050.0000.0110.0260.0000.3190.3190.3840.5610.561-0.1870.0020.0020.073-0.0270.0030.0000.0120.0000.0100.0000.0000.0000.0190.0000.0000.0350.0300.0470.0150.0160.0270.092-0.0100.1440.1490.0280.0001.000

Missing values

2025-05-07T18:18:03.039257image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-05-07T18:18:03.126137image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

edadimporte_solicitadoduracion_creditoantiguedad_empleadoingresospct_ingresotasa_interesestado_creditoantiguedad_clientegastos_ult_12mlimite_credito_tcpersonas_a_cargosituacion_vivienda_ALQUILERsituacion_vivienda_HIPOTECAsituacion_vivienda_OTROSsituacion_vivienda_PROPIAobjetivo_credito_EDUCACIÓNobjetivo_credito_INVERSIONESobjetivo_credito_MEJORAS_HOGARobjetivo_credito_PAGO_DEUDASobjetivo_credito_PERSONALobjetivo_credito_SALUDfalta_pago_Nfalta_pago_Yestado_civil_CASADOestado_civil_DESCONOCIDOestado_civil_DIVORCIADOestado_civil_SOLTEROestado_cliente_ACTIVOestado_cliente_PASIVOgenero_Fgenero_Mnivel_educativo_DESCONOCIDOnivel_educativo_POSGRADO_COMPLETOnivel_educativo_POSGRADO_INCOMPLETOnivel_educativo_SECUNDARIO_COMPLETOnivel_educativo_UNIVERSITARIO_COMPLETOnivel_educativo_UNIVERSITARIO_INCOMPLETOnivel_tarjeta_Bluenivel_tarjeta_Goldnivel_tarjeta_Platinumnivel_tarjeta_Silver
022350003123.0590000.5916.02136.01088.04010.02.0TrueFalseFalseFalseFalseFalseFalseFalseTrueFalseFalseTrueTrueFalseFalseFalseTrueFalseFalseTrueFalseFalseFalseFalseTrueFalseTrueFalseFalseFalse
121100025.096000.1011.14039.01144.012691.03.0FalseFalseFalseTrueTrueFalseFalseFalseFalseFalseTrueFalseTrueFalseFalseFalseTrueFalseFalseTrueFalseFalseFalseTrueFalseFalseTrueFalseFalseFalse
2233500024.0655000.5315.23136.01887.03418.03.0TrueFalseFalseFalseFalseFalseFalseFalseFalseTrueTrueFalseTrueFalseFalseFalseTrueFalseFalseTrueFalseFalseFalseFalseTrueFalseTrueFalseFalseFalse
3243500048.0544000.5514.27154.01314.09095.01.0TrueFalseFalseFalseFalseFalseFalseFalseFalseTrueFalseTrueTrueFalseFalseFalseTrueFalseFalseTrueTrueFalseFalseFalseFalseFalseTrueFalseFalseFalse
421250022.099000.257.14134.01171.03313.04.0FalseFalseFalseTrueFalseTrueFalseFalseFalseFalseTrueFalseFalseTrueFalseFalseTrueFalseTrueFalseFalseFalseFalseTrueFalseFalseTrueFalseFalseFalse
5263500038.0771000.4512.42121.0816.04716.03.0TrueFalseFalseFalseTrueFalseFalseFalseFalseFalseTrueFalseTrueFalseFalseFalseTrueFalseFalseTrueFalseFalseFalseFalseFalseTrueTrueFalseFalseFalse
6243500045.0789560.4411.11146.01330.034516.04.0TrueFalseFalseFalseFalseFalseFalseFalseFalseTrueTrueFalseTrueFalseFalseFalseTrueFalseFalseTrueTrueFalseFalseFalseFalseFalseFalseTrueFalseFalse
7243500028.0830000.428.90127.01538.029081.00.0TrueFalseFalseFalseFalseFalseFalseFalseTrueFalseTrueFalseFalseTrueFalseFalseTrueFalseFalseTrueFalseFalseFalseTrueFalseFalseFalseFalseFalseTrue
821160036.0100000.1614.74136.01350.022352.03.0FalseFalseFalseTrueFalseTrueFalseFalseFalseFalseTrueFalseFalseFalseFalseTrueTrueFalseFalseTrueFalseFalseFalseFalseFalseTrueTrueFalseFalseFalse
9223500046.0850000.4110.37136.01441.011656.02.0TrueFalseFalseFalseFalseTrueFalseFalseFalseFalseTrueFalseFalseFalseFalseTrueTrueFalseFalseTrueFalseFalseFalseFalseTrueFalseTrueFalseFalseFalse
edadimporte_solicitadoduracion_creditoantiguedad_empleadoingresospct_ingresotasa_interesestado_creditoantiguedad_clientegastos_ult_12mlimite_credito_tcpersonas_a_cargosituacion_vivienda_ALQUILERsituacion_vivienda_HIPOTECAsituacion_vivienda_OTROSsituacion_vivienda_PROPIAobjetivo_credito_EDUCACIÓNobjetivo_credito_INVERSIONESobjetivo_credito_MEJORAS_HOGARobjetivo_credito_PAGO_DEUDASobjetivo_credito_PERSONALobjetivo_credito_SALUDfalta_pago_Nfalta_pago_Yestado_civil_CASADOestado_civil_DESCONOCIDOestado_civil_DIVORCIADOestado_civil_SOLTEROestado_cliente_ACTIVOestado_cliente_PASIVOgenero_Fgenero_Mnivel_educativo_DESCONOCIDOnivel_educativo_POSGRADO_COMPLETOnivel_educativo_POSGRADO_INCOMPLETOnivel_educativo_SECUNDARIO_COMPLETOnivel_educativo_UNIVERSITARIO_COMPLETOnivel_educativo_UNIVERSITARIO_INCOMPLETOnivel_tarjeta_Bluenivel_tarjeta_Goldnivel_tarjeta_Platinumnivel_tarjeta_Silver
976622900034.0650000.149.63034.015577.013940.01.0FalseTrueFalseFalseTrueFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseTrueTrueFalseFalseTrueFalseFalseFalseTrueFalseFalseTrueFalseFalseFalse
976725950024.0610000.167.51050.014596.03688.01.0TrueFalseFalseFalseFalseTrueFalseFalseFalseFalseTrueFalseFalseFalseFalseTrueTrueFalseTrueFalseFalseFalseFalseFalseTrueFalseTrueFalseFalseFalse
976825950032.0680000.147.14040.015476.04003.02.0TrueFalseFalseFalseFalseFalseFalseTrueFalseFalseTrueFalseFalseFalseFalseTrueTrueFalseFalseTrueFalseFalseFalseFalseTrueFalseTrueFalseFalseFalse
976924950034.0586500.1416.49125.08764.04277.02.0TrueFalseFalseFalseFalseFalseFalseFalseFalseTrueTrueFalseFalseFalseTrueFalseFalseTrueFalseTrueTrueFalseFalseFalseFalseFalseTrueFalseFalseFalse
977022950041.0690000.1415.33120.09338.034516.02.0TrueFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseTrueTrueFalseFalseFalseFalseTrueFalseTrueFalseFalseFalseFalseFalseTrueFalseTrueFalseFalse
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